Network architecture.
The architecture of our network follows conventional Siamese trackers. We adopt the ResNet50 as the feature extractor. Features from layer 2, 3, 4 are used as inputs of the region proposal network (RPN), and these features are interpolated to the same spatial resolution. Also, a learned weight is used to aggregate these three correlation maps. The spatial resolution of search feature size is \(31 \times 31\) , the grid size in region mask operation is the same as this.
The anchor scale of RPN is set as 8, and the anchor ratio is set as \( [0.33, 0.5, 1, 2, 3]\) , ATSS [1]} is used to assign anchor label with the top-15 candidates. There are \(K=3125\)  candidate boxes in the prediction result of RPN.
